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in modern systems, as demonstrated in the figure, random access to memory is typically slower than sequential access to disk.
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SSD improves on this ratio by less than one order of magnitude. In a very real sense, all of the modern forms of storage improve only in degree, not in their essential nature, upon that most venerable and sequential of storage media: the tape.
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the highest-speed local network technologies have now surpassed most locally attached disk systems with respect to bandwidth, and network latency is naturally much lower than disk latency.
As a result, the performance cost of storing and retrieving data on other nodes in a network is comparable to (and in the case of random access, potentially far less than) the cost of using disk.
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21 Jan 13
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10 Mar 12
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00 gigabytes is enough to store at least the basic demographic information—age, sex, income, ethnicity, language, religion, housing status, and location, packed in a 128-bit record—for every living human being on the planet.
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The Web log records millions of visits a day to a handful of pages; the cellphone database stores time and location every 15 seconds for each of a few million phones;
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What makes most big data big is repeated observations over time and/or space.
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he fact that most large datasets have inherent temporal or spatial dimensions, or both, is crucial to understanding one important way that big data can cause performance problems, especially when databases are involved.
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Distributed Computing as a Strategy for Big Data
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he beauty of today’s mainstream computer hardware, though, is that it’s cheap and almost infinitely replicable. Today it is much more cost-effective to purchase eight off-the-shelf, “commodity” servers with eight processing cores and 128 GB of RAM each than it is to acquire a single system with 64 processors and a terabyte of RAM.
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28 Sep 11
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18 May 11
Nick GallThe Pathologies of Big Data (2009) http://bit.ly/jUXcKD /via @srisatish
I will take a stab at a meta-definition: big data should be defined at any point in time as “data whose size forces us to look beyond the tried-and-true methods that are prevalent at that time.” In the early 1980s, it was a dataset that was so large thatvia_delicious_20101217 bigdata definition pinboardimport20141106
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02 Mar 11
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18 Feb 11
Neil SaundersWhat is “big data” anyway? Gigabytes? Terabytes? Petabytes?
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28 Oct 10
korantengtradeoffs of big data in a human scale world
data scalability technology systems database performance scaling software modeling constraints architecture design strategy BestPractices
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31 May 10
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15 Jan 10
Antti PoikolaA database on the order of 100 GB would not be considered trivially small even today, although hard drives capable of storing 10 times as much can be had for less than $100 at any computer store.
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02 Oct 09
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The Pathologies of Big Data
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by Adam Jacobs | July 6, 2009
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Scale up your datasets enough and all your apps will come undone
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What are the typical problems and where do the bottlenecks generally surface?
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Dealing with Big Data
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Hard Limits
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Distributed Computing as a Strategy for Big Data
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A Meta-definition
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References
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Originally published in Queue vol. 7, no. 6
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06 Aug 09
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07 Jul 09
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